Engineering Manager
Wand AI
AWSAzureCloudGoogle Cloud Platform
Engineering Manager, Data
Renew Home
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $200,000 - $240,000 per year
Job Level
SeniorLead
Tech Stack
AirflowAmazon RedshiftApacheAWSCloudGoogle Cloud PlatformHadoopJavaKafkaPHPPostgresPythonRedisRubySparkTerraform
About the role
- Lead and mentor a team of data engineers, providing technical guidance, career development, and performance feedback to foster a high-performing and collaborative environment, including understanding leadership nuances, contributing to job descriptions, hiring plans, and participating in reviews and performance management actions.
- Architect and oversee the deployment of secure, scalable, and highly available batch and real-time data pipelines, ensuring alignment with business objectives and best practices, while personally delivering significant features and breaking down work into manageable deliverables.
- Guide the implementation and optimization of data lake architectures for handling structured and unstructured data from millions of thermostats, delegating tasks while maintaining overall accountability, and applying knowledge of the company's business to competitive advantage.
- Collaborate with development teams, data scientists, analysts, and other cross-functional stakeholders to integrate data engineering services into the broader system architecture and deliver clean, reliable data, advocating for technical solutions and motivating the team.
- Ensure the team strives for and achieves 99.99% uptime SLA for data systems, including managing and participating in on-call rotations, incident response, and the preparation of detailed incident reports, while providing solutions that meet standards of operational excellence.
- Uphold data quality, integrity, and compliance with governance standards, implementing processes and tools to monitor and enforce these across the team, and making recommendations for headcount planning.
- Manage the team's work across our technology stack, including Python,, Postgres, AWS/GCP services (CDK, ECS/EKS, RDS, Redshift, zeroETL,, S3 Tables, Athena, Iceberg, Glue, Flink, S3, SQS, SES, Pub/Sub, etc.), Prefect, Redis, Git, and Jira, demonstrating depth in 2+ areas and expertise in at least one layer of the technology stack.
- Facilitate the team's participation in agile development processes, including sprint planning, stand-up meetings, retrospectives, and one-on-ones, and make routine decisions easily while starting to handle more ambiguous choices.
- Handle resource allocation, project prioritization, hiring, and onboarding to build and maintain a talented data engineering team, familiar with company policies like anti-harassment and employee review cycles.
- Stay abreast of industry trends in data engineering and cloud technologies, championing continuous improvement and innovation within the team, gaining industry-wide knowledge and applying it to refine processes.
Requirements
- 8+ years of industry experience in data engineering or related fields, with at least 2-3 years in a leadership or management role overseeing technical teams (BS and 6-12 years of work experience preferred; MS counts as 1 year of experience).
- Bachelor's or Master's degree in computer science or equivalent experience in the software industry.
- Proven track record as a self-starter who identifies strategic opportunities, drives initiatives, and empowers teams to implement solutions that enhance operational excellence, capable of dealing with moderately complex area issues.
- Hands-on experience in building and managing scalable batch and real-time data pipelines using structured and unstructured data, with familiarity in orchestration tools like Prefect, Airflow, or Dagster, and gaining proficiency in all areas of the product and technology applications.
- Comfort balancing leadership and technical execution. Willing to engage directly in design and implementation work while effectively managing, mentoring, and enabling the team.
- Expertise in streaming technologies such as Apache Kafka, AWS Kinesis, Apache Flink, or GCP Pub/Sub.
- Strong knowledge of data lake architectures and technologies (e.g., AWS S3, AWS Glue, Delta Lake, or similar), knowledgeable of multiple product areas with depth in 2+ areas, and able to develop specific, well-defined problem statements for large unstructured problems.
- Demonstrated ability to lead database performance analysis and optimization, including query tuning, indexing, and resource management, preferably with Redshift and Postgres, as a point person on at least one key area.
- Proficiency in infrastructure-as-code tools like CDK and Terraform for automating deployments and management.
- Solid software engineering foundation with proficiency in programming languages such as Python, Java, PHP, or Ruby, and the ability to design to spec and deliver full-featured products or modules.
- Excellent leadership and communication skills, with experience in mentoring engineers, collaborating across teams, providing guidance on data infrastructure best practices, motivating smaller teams, and presenting to larger groups as part of a team.
- Commitment to fostering a culture of continuous learning, keeping the team updated on advancements in cloud infrastructure, database technologies, and data engineering processes, while understanding your own leadership style and leveraging it to develop and manage small teams.
- Ability to make decisions with incomplete data and understand when it's important to act without a clear choice, while being comfortable with ambiguous situations.
- Bonuses:
- Familiarity with data warehousing best practices and advanced Redshift features (e.g., Spectrum, workload management).
- Exposure to machine learning pipelines or big data frameworks like Apache Spark or Hadoop.
- Contributions to open-source data projects or relevant certifications (e.g., AWS Certified Data Analytics, GCP Professional Data Engineer).
Benefits
- A full-time position, with a competitive salary based on experience.
- Fully remote work environment with home office set-up allowance.
- Real and lived work-life balance - Company perks include no pre-set vacation limits (with a top-down culture of taking meaningful PTO every year!), parental leave benefits, and a corporate value of working sustainably and putting families first.
- Competitive benefits package that includes numerous health and wellness benefits.
- 401(k) plan, with employer contributions to the same.
- Opportunity to work with amazing people who are passionate about their mission, thriving in a fully-remote work environment, and learning and growing every day.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data engineeringdata pipelinesdata lake architecturestreaming technologiesdatabase performance analysisinfrastructure-as-codeprogramming languagesquery tuningorchestration toolscloud technologies
Soft skills
leadershipmentoringcommunicationcollaborationdecision makingproblem solvingteam motivationstrategic thinkingcontinuous learningperformance management
Certifications
AWS Certified Data AnalyticsGCP Professional Data Engineer
